Transform domain channel state information feedback

ABSTRACT

The generation of a channel state information report is provided. The generation includes transmitting reference signals to a user equipment, and receiving a reported set of quantized weighting coefficients, each of the weighting coefficients corresponding to a respective beam index and a respective tap index, where a set of beams based on the received reference signals is selected, where each of the beams corresponds to a discrete Fourier transform vector, and where each of the beams has a corresponding beam index. The tap index corresponds to a member of a Fourier basis set, where at least two subsets of the reported set of weighting coefficients are quantized according to separate quantization procedures.

FIELD OF THE INVENTION

The present disclosure is directed to a method and apparatus related tochannel state information feedback, including the generation of achannel state information report having weighting coefficients whichmake use of multiple separate quantization procedures.

BACKGROUND OF THE INVENTION

Presently, user equipment, such as wireless communication devices,communicate with other communication devices using wireless signals,such as within a network environment that can include one or more cellswithin which various communication connections with the network andother devices operating within the network can be supported. Networkenvironments often involve one or more sets of standards, which eachdefine various aspects of any communication connection being made whenusing the corresponding standard within the network environment.Examples of developing and/or existing standards include new radioaccess technology (NR), Long Term Evolution (LTE), Universal MobileTelecommunications Service (UMTS), Global System for MobileCommunication (GSM), and/or Enhanced Data GSM Environment (EDGE).

In an effort to enhance system performance, more recent standards havelooked at different forms of spatial diversity including different formsof multiple input multiple output (MIMO) systems, which involve the useof multiple antennas at each of the source and the destination of thewireless communication for multiplying the capacity of the radio linkthrough the use of multipath propagation. Such a system makesincreasingly possible the simultaneous transmission and reception ofmore than one data signal using the same radio channel.

As part of supporting MIMO communications, user equipment can make useof channel state information codebooks, which help to define the natureof the adopted beams, which are used to support a particular dataconnection. Higher rank codebooks can sometimes be used to enhancesystem performance, but often at the price of an increase in the amountof feedback overhead.

In at least some wireless communication systems, channel stateinformation (CSI) feedback is used to report on current channelconditions. This can be increasingly useful in frequency divisionduplexing (FDD) and frequency division multiple access (FDMA) systemswhere the downlink (DL) and uplink (UL) channels are not reciprocal.With multi-user (MU)-MIMO and spatial multiplexing, a receiving device,such as a user equipment (UE), may need to report channel conditions formultiple channels or beams. Accordingly, much overhead may be dedicatedto CSI reporting in MU-MIMO and spatial multiplexing systems.

The present inventors have recognized that improved methods forefficiently coding a channel state information (CSI) codebook may bebeneficial, as well as apparatuses and systems that perform thefunctions of the methods. The present inventors have further recognizedthat one such method (e.g., of a user equipment) can includecommunicating with a transmit-receive point (TRP) over a radio accessnetwork using spatial multiplexing. Here, multiple transmission layersmay be transmitted at a time, each transmission layer comprisingmultiple beams. The method can include transforming a set offrequency-domain precoding vectors to generate a set of coefficients ina compressed basis. It may be further beneficial for the method to alsoinclude quantizing the compressed basis coefficients depending on theirindex relative to indices of dominant compressed basis coefficients andthe beam. Indications of the quantized basis coefficients along withtheir indices may then be fed back from the UE to the gNodeB (gNB) asprecoding matrix information.

SUMMARY

The present application provides a method in a user equipment forgenerating a channel state information report. The method includesreceiving reference signals transmitted from a base station. A set ofbeams are selected based on the received reference signals, each of thebeams corresponding to a discrete Fourier transform vector, wherein eachof the beams has a corresponding beam index. A set of quantizedweighting coefficients are reported, each of the weighting coefficientscorresponding to a respective beam index and a respective tap index. Thetap index corresponds to a member of a Fourier basis set. At least twosubsets of the reported set of weighting coefficients are quantizedaccording to separate quantization procedures.

According to another possible embodiment, a user equipment in acommunication network, which includes one or more base stations, isprovided. The user equipment includes a transceiver that receivesreference signals transmitted from one of the one or more base stations.The user equipment further includes a controller that selects a set ofbeams based on the received reference signals. Each of the beamscorresponds to a discrete Fourier transform vector, wherein each of thebeams has a corresponding beam index. The transceiver further reports tothe network a set of quantized weighting coefficients. Each of theweighting coefficients correspond to a respective beam index and arespective tap index. The tap index corresponds to a member of a Fourierbasis set, and at least two subsets of the reported set of weightingcoefficients are quantized according to separate quantizationprocedures.

According to a further possible embodiment, a method in a network entityis provided. The method includes transmitting reference signalstransmitted to the user equipment, and receiving a reported set ofquantized weighting coefficients. Each of the weighting coefficientscorresponds to a respective beam index and a respective tap index. A setof beams based on the received reference signals is selected, where eachof the beams corresponds to a discrete Fourier transform vector, andwhere each of the beams has a corresponding beam index. The tap indexcorresponds to a member of a Fourier basis set. At least two subsets ofthe reported set of weighting coefficients are quantized according toseparate quantization procedures.

According to a still further possible embodiment, a network entity isprovided. The network entity includes a controller, and a transceiver,where the transceiver transmits a reference signal transmitted from oneof the one or more base stations, and receives a reported set ofquantized weighting coefficients, each of the weighting coefficientscorresponding to a respective beam index and a respective tap index. Aset of beams based on the received reference signals is selected, whereeach of the beams corresponds to a discrete Fourier transform vector,and where each of the beams has a corresponding beam index. The tapindex corresponds to a member of a Fourier basis set, and at least twosubsets of the reported set of weighting coefficients are quantizedaccording to separate quantization procedures.

These and other features, and advantages of the present application areevident from the following description of one or more preferredembodiments, with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

A more particular description of the embodiments briefly described abovewill be rendered by reference to specific embodiments that areillustrated in the appended drawings. Understanding that these drawingsdepict only some embodiments and are not therefore to be considered tobe limiting of scope, the embodiments will be described and explainedwith additional specificity and detail through the use of theaccompanying drawings, in which:

FIG. 1 is a schematic block diagram illustrating one embodiment of awireless communication system for efficiently coding a CSI codebook andpreparing a codeword therefrom;

FIG. 2 is a diagram illustrating time domain taps including dominant andadjacent taps along with beam dependent windows;

FIG. 3 is a diagram illustrating a range of tap indices from which tapindices are reported;

FIG. 4 is a block diagram illustrating one exemplary embodiment ofantenna elements;

FIG. 5 is a flow diagram in a user equipment for generating a channelstate information report;

FIG. 6 is a flow diagram in a network entity associated with receiving achannel state information report from the user equipment; and

FIG. 7 is an example block diagram of an apparatus according to apossible embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT(S)

While the present disclosure is susceptible of embodiment in variousforms, there is shown in the drawings and will hereinafter be describedpresently preferred embodiments with the understanding that the presentdisclosure is to be considered an exemplification of the invention andis not intended to limit the invention to the specific embodimentsillustrated.

Embodiments provide a method and apparatus for generation of a channelstate information report having weighting coefficients.

As will be appreciated by one skilled in the art, aspects of theembodiments may be embodied as a system, apparatus, method, or programproduct. Accordingly, embodiments may take the form of an entirelyhardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects.

For example, the disclosed embodiments may be implemented as a hardwarecircuit comprising custom very-large-scale integration (VLSI) circuitsor gate arrays, off-the-shelf semiconductors such as logic chips,transistors, or other discrete components. The disclosed embodiments mayalso be implemented in programmable hardware devices such as fieldprogrammable gate arrays, programmable array logic, programmable logicdevices, or the like. As another example, the disclosed embodiments mayinclude one or more physical or logical blocks of executable code whichmay, for instance, be organized as an object, procedure, or function.

Furthermore, embodiments may take the form of a program product embodiedin one or more computer readable storage devices storing machinereadable code, computer readable code, and/or program code, referredhereafter as code. The storage devices may be tangible, non-transitory,and/or non-transmission. The storage devices may not embody signals. Ina certain embodiment, the storage devices only employ signals foraccessing code.

Any combination of one or more computer readable medium may be utilized.The computer readable medium may be a computer readable storage medium.The computer readable storage medium may be a storage device storing thecode. The storage device may be, for example, but not limited to, anelectronic, magnetic, optical, electromagnetic, infrared, holographic,micromechanical, or semiconductor system, apparatus, or device, or anysuitable combination of the foregoing.

More specific examples (a non-exhaustive list) of the storage devicewould include the following: an electrical connection having one or morewires, a portable computer diskette, a hard disk, a random-access memory(RAM), a read-only memory (ROM), an erasable programmable read-onlymemory (EPROM or Flash memory), a portable compact disc read-only memory(CD-ROM), an optical storage device, a magnetic storage device, or anysuitable combination of the foregoing. In the context of this document,a computer readable storage medium may be any tangible medium that cancontain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

Reference throughout this specification to “one embodiment,” “anembodiment,” or similar language means that a particular feature,structure, or characteristic described in connection with the embodimentis included in at least one embodiment. Thus, appearances of the phrases“in one embodiment,” “in an embodiment,” and similar language throughoutthis specification may, but do not necessarily, all refer to the sameembodiment, but mean “one or more but not all embodiments” unlessexpressly specified otherwise. The terms “including,” “comprising,”“having,” and variations thereof mean “including but not limited to,”unless expressly specified otherwise. An enumerated listing of itemsdoes not imply that any or all of the items are mutually exclusive,unless expressly specified otherwise. The terms “a,” “an,” and “the”also refer to “one or more” unless expressly specified otherwise.

Furthermore, the described features, structures, or characteristics ofthe embodiments may be combined in any suitable manner. In the followingdescription, numerous specific details are provided, such as examples ofprogramming, software modules, user selections, network transactions,database queries, database structures, hardware modules, hardwarecircuits, hardware chips, etc., to provide a thorough understanding ofembodiments. One skilled in the relevant art will recognize, however,that embodiments may be practiced without one or more of the specificdetails, or with other methods, components, materials, and so forth. Inother instances, well-known structures, materials, or operations are notshown or described in detail to avoid obscuring aspects of anembodiment.

Aspects of the embodiments are described below with reference toschematic flowchart diagrams and/or schematic block diagrams of methods,apparatuses, systems, and program products according to embodiments. Itwill be understood that each block of the schematic flowchart diagramsand/or schematic block diagrams, and combinations of blocks in theschematic flowchart diagrams and/or schematic block diagrams, can beimplemented by code. This code may be provided to a processor of ageneral-purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the schematic flowchartdiagrams and/or schematic block diagrams.

The code may also be stored in a storage device that can direct acomputer, other programmable data processing apparatus, or other devicesto function in a particular manner, such that the instructions stored inthe storage device produce an article of manufacture includinginstructions which implement the function/act specified in the schematicflowchart diagrams and/or schematic block diagrams.

The code may also be loaded onto a computer, other programmable dataprocessing apparatus, or other devices to cause a series of operationalsteps to be performed on the computer, other programmable apparatus, orother devices to produce a computer implemented process such that thecode which execute on the computer or other programmable apparatusprovide processes for implementing the functions/acts specified in theschematic flowchart diagrams and/or schematic block diagram.

The schematic flowchart diagrams and/or schematic block diagrams in thefigures illustrate the architecture, functionality, and operation ofpossible implementations of apparatuses, systems, methods, and programproducts according to various embodiments. In this regard, each block inthe schematic flowchart diagrams and/or schematic block diagrams mayrepresent a module, segment, or portion of code, which includes one ormore executable instructions of the code for implementing the specifiedlogical function(s).

It should also be noted that, in some alternative implementations, thefunctions noted in the block may occur out of the order noted in theFigures. For example, two blocks shown in succession may, in fact, beexecuted substantially concurrently, or the blocks may sometimes beexecuted in the reverse order, depending upon the functionalityinvolved. Other steps and methods may be conceived that are equivalentin function, logic, or effect to one or more blocks, or portionsthereof, of the illustrated Figures.

The description of elements in each figure may refer to elements ofproceeding figures. Like numbers refer to like elements in all figures,including alternate embodiments of like elements.

A number of techniques have been proposed both in new radio (NR) Release15 and Release 16 for reducing the feedback overhead. At least one suchproposed technique involves only sending every other sub-band worth ofprecoding information and let the gNB use interpolation to obtainprecoding information in every other sub-band. Alternatively, sub-bandsizes can be made larger.

There have also been a number of proposals which transform the set ofprecoding vectors in the frequency domain to a compressed domain througha linear transformation. Due to the nature of the wireless channel,essentially its sparseness in the time domain, most of the energy in thecompressed domain is concentrated in a small number of coefficients (onthe order of 10 to 20 vs. 400 for frequency domain precoding feedback in10 MHz and 52 RBs). Only this small number of coefficients are fed back.Currently the linear transformations that have been proposed include onederived from the singular value decomposition (SVD) of the matrix formedfrom the frequency-domain precoding vectors and an oversampled discreteFourier transform (DFT) transformation. Once the gNB receives the fedback compressed-domain coefficients, the inverse of the lineartransformation is applied to give an approximation of the originalfrequency-domain precoding vectors.

Simulations of schemes based on DFT transformations show promise whereoverhead reduction of 50% may be possible thereby providing user packetthroughput and cell edge performance within a few percent of Release 15Type II performance. At least one aspect to reducing the overhead mayinvolve addressing the structure of coefficients in the time domain tochoose a more optimal set of coefficients to feed back and also takingadvantage of this structure to assign different levels of quantizationto different weighting coefficients.

In spatial multiplexing, the present inventors have observed that mostof the transmitted energy, e.g., 75% or more, is in the main beam ofeach transmission layer and that in about 85% of cases none of theselected beam vectors have zero amplitudes. The disclosed embodimentsleverage this information to improve coding efficiency of codebookparameters for CSI feedback using a Type II codebook. Type II codebookscan provide high resolution information about current channel conditionsand can be used in multi-user MIMO (“MU-MIMO”) scenarios, where spatialmultiplexing is used to increase the number of users and/or to increasethe transmission throughput (e.g., data bandwidth) for the users. Invarious embodiments, a transmitter will transmit a beamformedCSI-specific reference signal (CSI-RS) which the receiver uses tomeasure channel conditions. Generally, beamformed signals can include amain beam and one or more remaining beams.

FIG. 1 depicts a wireless communication system 100 for efficientlycoding a CSI codebook 150, according to embodiments of the disclosure.In one embodiment, the wireless communication system 100 includes atleast one remote unit 105, an access network 120 containing at least onebase unit 110, wireless communication links 115, and a mobile corenetwork 130. Even though a specific number of remote units 105, accessnetworks 120, base units 110, wireless communication links 115, andmobile core networks 130 are depicted in FIG. 1 , one of skill in theart will recognize that any number of remote units 105, access networks120, base units 110, wireless communication links 115, and mobile corenetworks 130 may be included in the wireless communication system 100.In another embodiment, the access network 120 contains one or morewireless local area network (WLAN) (e.g., Wi-Fi™) access points.

In one implementation, the wireless communication system 100 iscompliant with the 5G system specified in the 3rd generation partnershipproject (3GPP) specifications (e.g., “5G NR”). More generally, however,the wireless communication system 100 may implement some other open orproprietary communication network, for example, LTE or WiMAX, amongother networks. The present disclosure is not intended to be limited tothe implementation of any particular wireless communication systemarchitecture or protocol.

In one embodiment, the remote units 105 may include computing devices,such as desktop computers, laptop computers, personal digital assistants(PDAs), tablet computers, smart phones, smart televisions (e.g.,televisions connected to the Internet), smart appliances (e.g.,appliances connected to the Internet), set-top boxes, game consoles,security systems (including security cameras), vehicle on-boardcomputers, network devices (e.g., routers, switches, modems), or thelike. In some embodiments, the remote units 105 include wearabledevices, such as smart watches, fitness bands, optical head-mounteddisplays, or the like. Moreover, the remote units 105 may be referred toas subscriber units, mobiles, mobile stations, users, terminals, mobileterminals, fixed terminals, subscriber stations, UE, user terminals, adevice, or by other terminology used in the art. The remote units 105may communicate directly with one or more of the base units 110 viauplink (UL) and downlink (DL) communication signals. Furthermore, the ULand DL communication signals may be carried over the wirelesscommunication links 115.

The base units 110 may be distributed over a geographic region. Incertain embodiments, a base unit 110 may also be referred to as anaccess terminal, an access point, a base, a base station, a Node-B, aneNB, a gNB, a Home Node-B, a relay node, a device, or by any otherterminology used in the art. The base units 110 are generally part of aradio access network (RAN), such as the access network 120, that mayinclude one or more controllers communicably coupled to one or morecorresponding base units 110. These and other elements of the radioaccess network are not illustrated, but are well known generally bythose having ordinary skill in the art. The base units 110 connect tothe mobile core network 130 via the access network 120.

The base units 110 may serve a number of remote units 105 within aserving area, for example, a cell or a cell sector via a wirelesscommunication link 115. The base units 110 may communicate directly withone or more of the remote units 105 via communication signals.Generally, the base units 110 transmit downlink (DL) communicationsignals to serve the remote units 105 in the time, frequency, and/orspatial domain. Furthermore, the DL communication signals may be carriedover the wireless communication links 115. The wireless communicationlinks 115 may be any suitable carrier in licensed or unlicensed radiospectrum. The wireless communication links 115 facilitate communicationbetween one or more of the remote units 105 and/or one or more of thebase units 110.

In one embodiment, the mobile core network 130 is a 5G core (5GC) or theevolved packet core (EPC), which may be coupled to other data network125, like the Internet and private data networks, among other datanetworks. Each mobile core network 130 belongs to a single public landmobile network (PLMN). The present disclosure is not intended to belimited to the implementation of any particular wireless communicationsystem architecture or protocol.

The mobile core network 130 includes several network functions (NFs). Asdepicted, the mobile core network 130 includes an access and mobilitymanagement function (AMF) 135, a session management function (SMF) 140,and a user plane function (UPF) 145. Although a specific number of AMFs135, SMFs 140, and UPFs 145 are depicted in FIG. 1 , one of skill in theart will recognize that any number and type of network function may beincluded in the mobile core network 130.

The AMF 135 provides services such as UE registration, UE connectionmanagement, and UE mobility management. The SMF 140 manages the datasessions of the remote units 105, such as a protocol data unit (PDU)session. The UPF 145 provides user plane (e.g., data) services to theremote units 105. A data connection between the remote unit 105 and adata network 125 is managed by a UPF 145.

To support spatial multiplexing and MU-MIMO, the remote unit 105provides CSI feedback to the base unit 110 using a Type II codebook. Asdiscussed above, the remote unit 105 selects a codeword 155 from the CSIcodebook 150. Here, the access network 120 and the remote units 105 allhave copies of the same CSI codebook 150, wherein the remote unit 105provides CSI feedback by transmitting a codeword 155 from the CSIcodebook 150.

Consider an orthogonal frequency division multiplexing (OFDM) systemwhere the number of antenna ports is 2 N₁×N₂, where the quantities, N₁,N₂ denote the number of dual-polarized antenna elements in twodimensions respectively. The factor of 2 accounts for the antenna arraybeing composed of two antenna elements, each sensitive to orthogonalpolarization (e.g. horizontal and vertical). The received signal at theN_(r) antennas of the UE can be represented as

y_(n) = H_(n)W_(n)x_(n)

where H_(n) is the N_(r)×2 N₁N₂ baseband channel between the gNB and theUE, W_(n) is the precoding matrix applied at the gNB, and W_(n) is a R×1vector of modulation symbols where R is the number of layers to betransmitted. The subscript n denotes a subcarrier or sub-band index. InLTE Release 10-15 as well as in NR systems, the precoding matrix W_(n)is the product of two matrices W_(n)=W₁W_(2,n) where the first precodingmatrix W₁ is independent of frequency and has the form

$W_{1} = \begin{bmatrix}B & 0 \\0 & B\end{bmatrix}$

where B is a N₁N₂×L matrix with L orthogonal columns. The columns of W₁corresponds to 2 L “beams”. This term comes from one choice of B whereits columns are an orthogonal subset of the oversampled DFT vectors andtherefore spatial beams are overlapping in spatial frequency, each witha spatial direction of maximum response. The block diagonal structure ofW₁ is due to the use of dual polarization with both polarizations havingthe same set of beams. The B matrix can be the identity matrix in whichcase L is equal to N₁N₂. The matrix 2 L×R matrix W₂, providesfrequency-dependent precoding of the R layers of x_(n) where theprecoding is applied to the 2 L beams. Each column of W₂, is an 2 L×1frequency-dependent vector which precodes one layer of informationsymbols, i.e. one element of x_(n)

In a closed-loop precoding system the measurement of reference signalstransmitted by the gNb enables the UE to estimate the channel matrixH_(n) over a set of frequencies. For example, when reference signals aresent in each of 12 subcarrier-wide resource blocks (RBs), the channelmatrix at index n represents the channel in the nth RB. The UE then usesthis information to determine W (equivalently B) as well W_(2,n) whichin some sense better optimizes the transmission from the gNb. The UE mayfeed back an indication of the L DFT vectors in B out of a collection oforthogonal beam sets.

The UE may also feed back an indication of the precoding vectors inW_(2,n), one for each layer over a set of, for example RBs spanning thefrequency band of operation. The columns of the frequency-dependentprecoding matrix W_(2,n)=[W_(2,n,1) W_(2,n,2) . . . W_(2,n,R)] can alsobe expressed as the product of a frequency-independent component,W_(2,0,r) and a frequency dependent term W′_(2,n,r)

W_(2, n, r) = W_(2, 0, r) ⊙ W_(2, n, r)^(′)

where the symbol ⊚ denote the Schur (also referred to as Hadamard)product which is the element-by-element of two matrices. This allows a“wideband” gain term, W_(2,0,r), to be signaled separately from theterm, W′_(2,n,r), which captures the frequency dependent variation. Thecomponents of the vector W_(2,n,r) may also be scaled by the strongestelement corresponding to a strongest spatial beam. An index from 1 to Lindicating the wideband strongest beam can also signaled by the UE. Onewideband strongest beam per layer may be signaled.

The frequency-dependent W_(2,n,r) typically contains phase informationthat instructs the gNb of the relative phase between beams to use whentransmitting to the UE. Because an indication of W′_(2,n,r) must be sentfor every sub-band, the overhead due to these indications can becomelarger especially when the bandwidth of operation is large.

The elements of a precoding vector W_(2,n,r) are typically correlated inthe sense that their phase typically follows a roughly linear trajectoryat least for channels typically used in wireless networks.Mathematically, denoting W′_(2,n,r)(l) 1≤l≤2 L as the lth element of theprecoding vector for layer r at sub-band n, the phases of the sequenceW_(2,1,r)(l), W_(2,2,r)(l), . . . , W_(2,N,r)(l) typically have a lineartrend. This correlation can be attributed to the channel between gNB andUE being linear-shift invariant with a set of dominant taps. For exampleperfect linear phase across frequency occurs when the channel modelcontains a single delay tap. The high degree of correlation suggeststhat a vector of precoding weights across sub-bandsW_(2,r)(l)=[W_(2,1,r)(l), W_(2,2,r)(l), . . . , W_(2,N) _(sb)_(,r)(l)]^(T) can be expressed as a linear combination of a small numberof vectors chosen from an orthogonal basis, termed the compressed basisbelow. Taking the example of the single delay tap channel, the complexchannel coefficient along with the delay of the tap is sufficient tospecify the precoding vector W_(2,r)(l). In this case the compressedbasis is the DFT basis and the single tap coefficient can be obtainedwith an inverse Fourier transform of W_(2,r)(l). Other orthogonal basesare possible including one derived by the SVD of the correlation matrixof W_(2,r)(l)[w_(2,1,r)(l), w_(2,2,r)(l), . . . , w_(2,N) _(sb)_(,r)(l)]^(T) taken over beams and possibly ranks.

Instead of reporting an indication of W_(2,n) for all sub-bands n, theUE first applies a linear transformation denoted by the matrix V to itscomponent length N_(sb) vectors. The transformation is applied toW_(2,r)(l) for each of 2 L beams and each of R layers, forming thetransformed vectors w_(2,r) (l):

w_(2, r)(l) = VW_(2, r)(l), 1 ≤ l ≤ 2L, 1 ≤ r ≤ R

The transformation V can either be known ahead of time by the UE andgNB, e.g. defined in a standard, or in the case of the SVD methodmentioned above, signaled by the UE to the gNB.

As mentioned above, most of the energy in the vector w_(2,r)(l) isconcentrated in a small number of elements. Instead of feeding back allof the N_(sb) elements of the vector w_(2,r)(l) it is possible to onlyfeed back the elements of w_(2,r)(l) which have significant energy. Withthis approach it is also beneficial for the UE to send to the gNB theset of indices of the basis functions whose coefficients containsignificant energy. Mathematically, this can be described as the UEfeeding back an indication of an approximate version of w_(2,r)(l),denoted ŵ_(2,r)(l) where all but K_(r)(l) of the indices of ŵ_(2,r)(l)are zero and the corresponding indices, k_(r,m)(l), 1≤m≤K_(r)(l). Thisindication requires less overhead than that of either the fullfrequency-domain vectors W_(2,r)(l) or the complete transformed vectorsw_(2,r) (l). Additional methods of determining approximate weightvectors ŵ_(2,r)(l) from the transformed precoding vectors, w_(2,r)(l),will be described below.

Once the gNB receives the indications of k_(r,m)(l) and ŵ_(2,r)(l), thegNB can construct ŵ_(2,r)(l) and through the inverse transformation V⁻¹,an approximation Ŵ_(2,r)(l) to the precoding vectors W_(2,r)(l) for eachbeam l and for each layer r:

Ŵ_(2, r) = V⁻¹ŵ_(2, r)(l), 1 ≤ l ≤ 2L, 1 ≤ r ≤ R

An approximate frequency-dependent precoding matrix, Ŵ_(2,n,r) can thenbe formed from the columns Ŵ_(2,r)(l). As stated above, the gNB alsoobtains the indication of the beams which define the matrix B which interm form W₁. From W₁ and Ŵ_(2,n,r), the gNB can then obtain thecomplete precoder recommended by the UE:

Ŵ = W₁Ŵ₂

In one embodiment the transformation, V, to the compressed basis set isthe inverse DFT. In this cases the indication of the basis functions aredelay values which are represented as integer multiples of a fundamentalsampling time. The weights to be fed back are the complex-valued gainsof the taps corresponding to these delays.

In one embodiment the precoding vectors in the frequency domain can benormalized by that of a single dominant beam. In this case thetransformation is applied to a normalized version of the frequencydomain precoding vectors, {tilde over (W)}_(2,r)(l):

${{\overset{\sim}{W}}_{2,r}(l)} = \frac{W_{2,r}(l)}{W_{2,r}(1)}$

where here it is assumed that the dominant beam has index ‘1’. Thedominant beam may be different for different ranks. When this isperformed, the elements of the precoding vector corresponding to thefirst beam are unity across frequency and there is no need to transformthis vector to the compressed domain since it is known to be unity inthe frequency domain. When the compressed domain is the time domain,this normalization has the additional effect of shifting the delays ofnon-dominant beams. For example if the dominant beam consists of asingle delay in the time domain, then normalization by this beam in thefrequency domain will cause the delays of all other beams to be shiftedsuch that a delay of zero is the delay of the dominant path.

In addition to forming an approximation, ŵ_(2,r)(l), of the transformedprecoding vectors w_(2,r)(l) by setting components of ŵ_(2,r)(l) equalto the corresponding components of w_(2,r)(l) for those components whohave significant energy, i.e., those components which have absolutevalue above a threshold, other methods of forming approximations tow_(2,r)(l) are possible. In the following an embodiment is describedwhere the transformation, V, which transforms the precoding vectors fromthe frequency domain to the compressed basis, can be derived from anoversampled DFT matrix by selecting an orthogonal set of columns.Therefore the matrix V is of the form

${V_{m,n} = e^{j\frac{2\pi{({m_{0} + {Om}})}n}{ON_{sb}}}},{0 \leq m \leq {N_{sb} - 1}},{0 \leq n \leq N_{s,{b - 1}}}$

where O is the oversampling factor and m₀, 0≤m₀<O−1 is the samplingoffset. The same techniques described below can be applied with otherchoices of transformation. In this embodiment an indication of thesampling offset m₀ is also fed back to the gNB along with theindications of the weighting coefficients ŵ_(2,r)(l) and correspondingindices of the basis functions, k_(r,m)(l), which in the case of the DFTlinear transformation are termed taps.

The transformed vector can be expressed in terms of its components as

w_(2, r)(l) = [w_(2, 1, r)(l), w_(2, 2, r)(l), …, w_(2, N_(sb), r)(l)]^(T)

where l is the beam index and r is the layer index. Typical magnitudesquare of w_(2,n,r)(l) are plotted in FIG. 2 for a fixed layer r anddifferent beams in the vertical direction and tap index n along thehorizontal direction. For a fixed beam one or more dominant taps 201 arepresent where |w_(2,n,r)(l)|² is relatively large. The adjacent taps 203have smaller |w_(2,n,r)(l)|² than that of the dominant tap but stilllarger than taps further away from the dominant tap. It may bebeneficial to feed back weighting coefficients only for those taps withsignificant energy, which from the figure are the taps whose indices arewithin a window of a dominant tap. In addition it may be beneficial toquantize the taps with finer quantization (more quantization levels) forlarger transformed precoding coefficient magnitude |w_(2,n,r)(l)|² andfewer quantization levels for taps with low transformed precodingcoefficient magnitude |w_(2,n,r)(l)|². In addition to taps being weakerthe farther away from a dominant path, some paths are statisticallyweaker than others. For example, if the scaling strategy above isemployed, then the strongest beam is used as a reference and weightingcoefficients are fed back for the remaining 2 L−1 beams beginning withbeam 2. In dual-polarized systems, the beam with the same DFT column asthe dominant beam, but the orthogonal polarization, tends to be largerthan the remaining 2 L−1 beams. Therefore the number of quantizationlevels used for a beam can be based on the proximity of a tap to adominant tap as well as its beam index.

Referring again to FIG. 2 , the set of beams are divided into beam set a205 and beam set b 207. The number of beam sets could be more than twohowever. In FIG. 2 the scaling scheme described above is assumed andtherefore no weighting vectors are fed back for the first beam.Therefore 2 L−1 beams are shown with beam indexing beginning with beamindex 2. Scaling by the dominant beam however is not required in whatfollows. Each beam set has a corresponding tap window, the tap windowfor beam set a is denoted as W_(a) 209 and the tap window for beam set b211 is denoted as W_(b). Taps which follow outside the tap window do nothave their weighting coefficients reported. The weighting vectorreported by the UE for a tap within a tap window is quantized with aquantization scheme that is dependent upon its beam set and whether itis a dominant tap or an adjacent tap. For example, dominant taps of abeam within beam set a are quantized with one quantization scheme. Aquantization scheme can consist of quantizing the magnitude and phaseseparately or quantizing the real and imaginary parts separately. Ineither case, the quantizing scheme is also characterized by the numberof quantization levels used for each part. The number of quantizationlevels can also be expressed as the number of bits needed to express theindex of quantization level in a binary representation. Adjacent taps ofbeam set a that are within the tap window W_(a) are quantized with adifferent quantization scheme than the dominant tap. They may, forexample, be quantized with fewer bits of amplitude or phase levels. Inaddition the reference (or ‘full scale’) for quantization for adjacenttaps can be the quantized dominant path within the window.

Taps belonging to beam set b that are within a window W_(b) and are thedominant paths can be quantized with a different quantization schemethan either the dominant or adjacent taps in beam set a. Taps belongingto beam set b that are within a window W_(b) and are adjacent paths canbe quantized with a different quantization scheme than either thedominant or adjacent taps in beam set a or the dominant taps in beam setb.

In addition to the elements of the quantized transformed precodingvectors ŵ_(2,r)(l) which are within a tap window and thereforepotentially non-zero, the UE may also feed back the dominant tap indicesfor each beam. If a dominant tap index can be any index of thetransformed precoding vector, then the number of bits needed torepresent the tap index is log₂ (└N_(sb)┘) where └ ┘ denotes the ceilingfunction. If the scaling strategy described is employed or for channelswith low delay spread, it may be unlikely that dominant taps occuroutside a given range. Referring to FIG. 3 , the dominant taps 301 for aset of 2 L−1 beams are shown. Indices of dominant taps 303 within aninterval of integer indices, called the range R 303, are fed back to thegNB. The range 305 can be signaled by the gNB with control signaling,such as RRC signaling or layer 1 signaling used in NR. The lowest indexin the range may be 0 or 1. The largest index in the range can be thelargest index of a dominant path which can be fed back by the UE. Thenumber of elements in the range can be the number of different indicesthat a dominant path index fed back by the UE can take.

An alternative embodiment for reporting the indices of the dominant tapsis to feed back a set of delays D that has a number of members that isless than the number of beams, 2 L−1. In addition for each beam anindicator is fed back that indicates which one of the delays in D is thedelay of the dominant tap for that beam. For example D may be the set{0,1} and beams 2, 3, 4, 5, 6 may have dominant tap delays of 0 whilebeam 7 has dominant tap delay 1. In this case four bits are used to senda representation of D and one bit is used for each beam for a total of4+7=11. This is in contrast to sending a 2 bit representation for everybeam which is 14 bits.

Another alternative embodiment for reporting the indices of the dominanttaps is to feed back a single delay corresponding to the delay of adominant tap of one beam or a fixed value. This delay is represented ina fixed number of bits. A second delay is represented as the differencebetween the second delay and the first delay. This delay is representedin a number of bits less than the first delay. Additional delays arerepresented as the difference relative to the previous delay.Alternatively, additional delays are represented as the differencerelative to the first delay.

For a user equipment, such as remote unit 105, a transceiver can be usedto communicate with one or more network functions of a mobilecommunication network. The transceiver can operate under the control ofa processor to transmit messages, data, and other signals and also toreceive messages, data, and other signals. For example, the processormay selectively activate the transceiver (or portions thereof) atparticular times in order to send and receive messages. To supportspatial multiplexing and beamforming, the transceiver may includemultiple transmitters and/or multiple receivers.

FIG. 4 depicts an array 400 of antenna elements 405 for efficientlycoding a CSI codebook, according to various embodiments of thedisclosure. Here, the antenna elements 405 are arranged into a 4×4 grid.As depicted, each antenna elements 405 has an index and the location ofeach antenna elements may be described using coordinates of a firstdimension 410 and a second dimension 415. For example, the antennaelements 405 of index 7 may be described using the coordinates {3,1} andthe antenna elements 405 of index 12 may be described using thecoordinates {3,0}. Note that the beam index may be identified using a4-bit value. In some embodiments, each antenna elements 405 is adual-polarized antenna element comprising two physical elements, eachsensitive to orthogonal polarization.

An antenna port may correspond to one or more physical network elements.In certain embodiments, an antenna port corresponds to a set oforthogonally arranged antenna elements, such that the antenna port mayproduce a beam with a first polarization or a second polarizationorthogonal to the first polarization. Thus, a dual-polarized antennaelement may correspond to two antenna ports, one for each orthogonalpolarization. In various embodiments, preparing a CSI codeword includesidentifying a beam index of the main beam of a transmission layer. Here,the beam index may be the index of the corresponding (dual-polarized)antenna element.

FIG. 5 illustrates a flow diagram 500 in a user equipment for generatinga channel state information report. The method includes receiving 502reference signals transmitted from a base station. A set of beams areselected 504 based on the received reference signals, each of the beamscorresponding to a discrete Fourier transform vector, wherein each ofthe beams has a corresponding beam index. A set of quantized weightingcoefficients are reported 506, each of the weighting coefficientscorresponding to a respective beam index and a respective tap index. Thetap index corresponds to a member of a Fourier basis set 508. At leasttwo subsets of the reported set of weighting coefficients are quantizedaccording to separate quantization procedures 510.

In some instances, the weighting coefficients belonging to differentsubsets have distinct corresponding beam index values. In some of theseinstances, the number of subsets is 2, and wherein the beam index valuescorresponding to the first subset of weighting coefficients are includedin a first half of the ordered beam indices, and the beam index valuescorresponding to the second subset of weighting coefficients areincluded in a second half of the ordered beam indices. The discreteFourier transform vectors of the selected set of beams corresponding tothe first and second subsets of weighting coefficients in some instancescan be identical.

In others of these instances, the number of subsets is 2, and whereinthe number of beam index values corresponding to the first subset ofweighting is equal to the number of beam index values corresponding tothe second subset of weighting coefficients. The discrete Fouriertransform vectors of the selected set of beams corresponding to thefirst and second subsets of weighting coefficients in some instances canbe identical. The quantization procedures in some instances can assigndifferent levels of quantization to different weighting coefficients.

In some instances, the Fourier basis set is one of a discrete Fouriertransform or an inverse discrete Fourier transform basis sets.

In some instances, the quantization procedures assign different levelsof quantization to different weighting coefficients.

In some instances, one of the weighting coefficients corresponding to adominant tap index within a subset has a separate quantization procedurethan the remaining weighting coefficients in the subset.

FIG. 6 illustrates a flow diagram 600 in a network entity associatedwith receiving a channel state information report from the userequipment. The method includes transmitting 602 reference signalstransmitted to the user equipment, and receiving 604 a reported set ofquantized weighting coefficients. Each of the weighting coefficientscorresponds to a respective beam index and a respective tap index. A setof beams based on the received reference signals is selected, where eachof the beams corresponds to a discrete Fourier transform vector, andwhere each of the beams has a corresponding beam index. The tap indexcorresponds to a member of a Fourier basis set 606. At least two subsetsof the reported set of weighting coefficients are quantized according toseparate quantization procedures 608.

It should be understood that, notwithstanding the particular steps asshown in the figures, a variety of additional or different steps can beperformed depending upon the embodiment, and one or more of theparticular steps can be rearranged, repeated or eliminated entirelydepending upon the embodiment. Also, some of the steps performed can berepeated on an ongoing or continuous basis simultaneously while othersteps are performed. Furthermore, different steps can be performed bydifferent elements or in a single element of the disclosed embodiments.

FIG. 7 illustrates an example block diagram of an apparatus 700, such asthe wireless communication device 105, according to a possibleembodiment. The apparatus 700 can include a housing 710, a controller720 within the housing 710, audio input and output circuitry 730 coupledto the controller 720, a display 740 coupled to the controller 720, atransceiver 750 coupled to the controller 720, an antenna 755 coupled tothe transceiver 750, a user interface 760 coupled to the controller 720,a memory 770 coupled to the controller 720, and a network interface 780coupled to the controller 720. The apparatus 700 can perform the methodsdescribed in all the embodiments.

The display 740 can be a viewfinder, a liquid crystal display (LCD), alight emitting diode (LED) display, a plasma display, a projectiondisplay, a touch screen, or any other device that displays information.The transceiver 750 can include a transmitter and/or a receiver. Theaudio input and output circuitry 730 can include a microphone, aspeaker, a transducer, or any other audio input and output circuitry.The user interface 760 can include a keypad, a keyboard, buttons, atouch pad, a joystick, a touch screen display, another additionaldisplay, or any other device useful for providing an interface between auser and an electronic device. The network interface 780 can be aUniversal Serial Bus (USB) port, an Ethernet port, an infraredtransmitter/receiver, an IEEE 1394 port, a WLAN transceiver, or anyother interface that can connect an apparatus to a network, device, orcomputer and that can transmit and receive data communication signals.The memory 770 can include a random access memory, a read only memory,an optical memory, a solid state memory, a flash memory, a removablememory, a hard drive, a cache, or any other memory that can be coupledto an apparatus.

The apparatus 700 or the controller 720 may implement any operatingsystem, such as Microsoft Windows®, UNIX®, or LINUX®, Android™, or anyother operating system. Apparatus operation software may be written inany programming language, such as C, C++, Java or Visual Basic, forexample. Apparatus software may also run on an application framework,such as, for example, a Java® framework, a .NET® framework, or any otherapplication framework. The software and/or the operating system may bestored in the memory 770 or elsewhere on the apparatus 700. Theapparatus 700 or the controller 720 may also use hardware to implementdisclosed operations. For example, the controller 720 may be anyprogrammable processor. Disclosed embodiments may also be implemented ona general-purpose or a special purpose computer, a programmedmicroprocessor or microprocessor, peripheral integrated circuitelements, an application-specific integrated circuit or other integratedcircuits, hardware/electronic logic circuits, such as a discrete elementcircuit, a programmable logic device, such as a programmable logicarray, field programmable gate-array, or the like. In general, thecontroller 720 may be any controller or processor device or devicescapable of operating an apparatus and implementing the disclosedembodiments. Some or all of the additional elements of the apparatus 700can also perform some or all of the operations of the disclosedembodiments.

The method of this disclosure can be implemented on a programmedprocessor. However, the controllers, flowcharts, and modules may also beimplemented on a general purpose or special purpose computer, aprogrammed microprocessor or microcontroller and peripheral integratedcircuit elements, an integrated circuit, a hardware electronic or logiccircuit such as a discrete element circuit, a programmable logic device,or the like. In general, any device on which resides a finite statemachine capable of implementing the flowcharts shown in the figures maybe used to implement the processor functions of this disclosure.

While this disclosure has been described with specific embodimentsthereof, it is evident that many alternatives, modifications, andvariations will be apparent to those skilled in the art. For example,various components of the embodiments may be interchanged, added, orsubstituted in the other embodiments. Also, all of the elements of eachfigure are not necessary for operation of the disclosed embodiments. Forexample, one of ordinary skill in the art of the disclosed embodimentswould be enabled to make and use the teachings of the disclosure bysimply employing the elements of the independent claims. Accordingly,embodiments of the disclosure as set forth herein are intended to beillustrative, not limiting. Various changes may be made withoutdeparting from the spirit and scope of the disclosure.

What is claimed is:
 1. A method in a network entity for communicatingwith a user equipment, the method comprising: transmitting referencesignals to the user equipment; receiving a reported set of quantizedweighting coefficients, each of the weighting coefficients correspondingto a respective beam index and a respective tap index, where a set ofbeams based on the reference signals transmitted to the user equipmentis selected, where each of the beams corresponds to a discrete Fouriertransform vector, and where each of the beams has a corresponding beamindex; wherein the tap index corresponds to a member of a Fourier basisset; wherein at least two subsets of the reported set of weightingcoefficients are quantized according to separate quantizationprocedures; wherein the weighting coefficients belonging to differentsubsets have distinct corresponding beam index values; and wherein thenumber of subsets is 2, and wherein the beam index values correspondingto the first subset of weighting coefficients are included in a firsthalf of ordered beam indices, and the beam index values corresponding tothe second subset of weighting coefficients are included in a secondhalf of the ordered beam indices, where the ordered beam indices includethe corresponding beam index of each of the beams from the set of beamsthat have been organized based upon a respective energy associated witheach of the corresponding beam index of each of the beams.
 2. The methodof claim 1, wherein the discrete Fourier transform vectors of theselected set of beams corresponding to the first and second subsets ofweighting coefficients are identical.
 3. The method of claim 1, whereinthe number of beam index values corresponding to the first subset ofweighting coefficients is equal to the number of beam index valuescorresponding to the second subset of weighting coefficients.
 4. Themethod of claim 3, wherein the discrete Fourier transform vectors of theselected set of beams corresponding to the first and second subsets ofweighting coefficients are identical.
 5. The method claim 3, wherein thequantization procedures assign different levels of quantization todifferent weighting coefficients.
 6. The method of claim 1, wherein theFourier basis set is one of a discrete Fourier transform or an inversediscrete Fourier transform basis sets.
 7. The method of claim 1, whereinthe quantization procedures assign different levels of quantization todifferent weighting coefficients.
 8. The method of claim 1, wherein oneof the weighting coefficients corresponding to a dominant tap indexwithin a subset has a separate quantization procedure than the remainingweighting coefficients in the subset.
 9. The method of claim 8, whereinthe separate quantization procedures include at least a finerquantization having more quantization levels, and a coarser quantizationhaving fewer quantization levels.
 10. The method of claim 1, whereinrespective inclusion in the first and second subset is dependent uponwhether the respective energy associated with each of the correspondingbeam index of each of the beams exceeds a predetermined threshold value.11. The method of claim 1, wherein respective inclusion in the first andsecond subset is dependent upon whether the respective energy associatedwith each of the corresponding beam index of each of the beams has azero coefficient value, or a non-zero coefficient value.
 12. A networkentity for communicating with a user equipment, the network entitycomprising: a controller; and a transceiver that transmits referencesignals to the user equipment, and receives a reported set of quantizedweighting coefficients, each of the weighting coefficients correspondingto a respective beam index and a respective tap index, wherein a set ofbeams based on the reference signals is selected, where each of thebeams corresponds to a discrete Fourier transform vector, and where eachof the beams has a corresponding beam index; wherein the tap indexcorresponds to a member of a Fourier basis set; wherein at least twosubsets of the reported set of weighting coefficients are quantizedaccording to separate quantization procedures; wherein the weightingcoefficients belonging to different subsets have distinct correspondingbeam index values; and wherein the number of subsets is 2, and whereinthe beam index values corresponding to the first subset of weightingcoefficients are included in a first half of ordered beam indices, andthe beam index values corresponding to the second subset of weightingcoefficients are included in a second half of the ordered beam indices,where the ordered beam indices includes the corresponding beam index ofeach of the beams from the set of beams that have been organized basedupon a respective energy associated with each of the corresponding beamindex of each of the beams.
 13. The network entity of claim 12, whereinthe discrete Fourier transform vectors of the selected set of beamscorresponding to the first and second subsets of weighting coefficientsare identical.
 14. The network entity of claim 12, wherein the number ofbeam index values corresponding to the first subset of weightingcoefficients is equal to the number of beam index values correspondingto the second subset of weighting coefficients.
 15. The network entityof claim 14, wherein the discrete Fourier transform vectors of theselected set of beams corresponding to the first and second subsets ofweighting coefficients are identical.
 16. The network entity of claim14, wherein the quantization procedures assign different levels ofquantization to different weighting coefficients.
 17. The network entityof claim 12, wherein the Fourier basis set is one of a discrete Fouriertransform or an inverse discrete Fourier transform basis sets.
 18. Thenetwork entity of claim 12, wherein the quantization procedures assigndifferent levels of quantization to different weighting coefficients.19. The network entity of claim 12, wherein one of the weightingcoefficients corresponding to a dominant tap index within a subset has aseparate quantization procedure than the remaining weightingcoefficients in the subset.
 20. The network entity of claim 19, whereinthe separate quantization procedures include at least a finerquantization having more quantization levels, and a coarser quantizationhaving fewer quantization levels.